Speech-based AI-driven Diagnostics and Rehabilitation for Oral and Oropharyngeal Cancer.

A Preliminary Study on the Phonetics of Resonance and Articulation Disorders Caused by Defects of the Oral and Maxillofacial Speech Organs and Speech Therapy

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT07347899

Acronym

speech omics

Enrollment

501

Registered

2026-01-16

Start date

2017-07-17

Completion date

2022-12-31

Last updated

2026-01-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Oral Cancer, Oropharyngeal Cancer

Keywords

speech signal analysis, diagnostic models, vowel acoustics, bio-inspired computing

Brief summary

Participants diagnosed with oral cancer, oropharyngeal cancer, or oral potentially malignant lesions, as well as healthy controls, had their speech audio recordings collected for the development and validation of AI-driven models for diagnosis and prognosis prediction of oral cancer and oropharyngeal cancer.

Detailed description

Participants were instructed to articulate three sustained vowels (/a/, /i/, /u/) repeatedly at a moderate volume and pace, with three repetitions per vowel and each utterance lasting at least one second. We developed a neuromorphic computing framework that orthogonally decomposes acoustic features into ultra-dimensional omics representations, enabling the characterization of both localized lesions and systemic physiological conditions. The study collected a comprehensive spectrum of biological profiles, including sociodemographic characteristics, tumor metrics, oral function-related factors, patient-reported outcome measures (PROMs), immunoinflammatory indices, and general health status indicators, to thoroughly investigate the paralinguistic representations of transformed speech omics features. These features were then rigorously evaluated for their clinical efficacy across multiple diagnostic tasks, including screening, early detection, pathological diagnosis, disease staging, and risk factor identification.

Interventions

None listed

Study design

Observational model

CASE_CONTROL

Time perspective

CROSS_SECTIONAL

Eligibility

Sex/Gender

ALL

Age

18 Years to 85 Years

Healthy volunteers

Yes

Inclusion criteria

* diagnosed as having OC or OPC regardless of concrete pathological subtype (e.g., epithelial, adenoid, odontogenic) * without a history of other tumor-related treatment before the initial evaluation, such as radiotherapy and chemotherapy * native Chinese speakers

Exclusion criteria

* hearing impairment * history of stuttering, cerebrovascular accident, brain trauma, neurodegenerative diseases * severe dental or maxillofacial deformity * cleft lip, cleft palate, and related post-treatment status * severe cardiology conditions, breathing/pulmonology disorders, psychiatric disorders or other illnesses preventing patients from receiving standard surgery

Design outcomes

Primary

Measure	Time frame	Description
AUC value	From enrollment to the report of surgical pathology，up to two weeks.	Area under the receiver operating characteristic curve (AUC) for discriminating OC/OPC from healthy controls

Countries

China

Outcome results